Senior Signal Integrity Engineer – Cryogenic Interconnects
NVIDIA is hiring a Senior Signal Integrity Engineer – Cryogenic Interconnects in Santa Clara, United States. It pays $168k-$265k a year and Level rates it ; you can apply on NVIDIA.
Level's read on this job
- Level rates this role Little AI ●○○○: aI is not part of the work.
- Level classifies it as a senior role.
- Level lists 2,700+ other open roles at NVIDIA.
AI in this role
We are now looking for a Senior Signal Integrity Engineer – Cryogenic Interconnects! NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI - the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can tackle, and that matter to the world. This is our life’s work, to amplify human imagination and intelligence.
This is a dynamic team working with state-of-the-art, unique technology. If you are someone that loves a challenge, come join this diverse team and help move the needle.
What you'll be doing:
Develop accurate 3D EM models for PCB and interconnect structures using tools such as HFSS
Simulate multi-layer PCB designs under cryogenic conditions
Define high-speed constraints, SI specifications, and design guidelines across RF, materials, and thermal domains
Work on next-generation cryogenic interconnect solutions for ultra-high-speed communication
Collaborate closely with SI, materials, mixed-signal, and system teams to drive end-to-end interconnect performance
Perform lab characterization and validation using network analyzers and other measurement tools
Correlate simulation results with hardware measurements to improve modeling accuracy
Contribute to system-level understanding of interconnect behavior across PCB, package, and system domains
What we need to see:
MS/PhD in Electrical Engineering or equivalent experience
5+ years of experience
Strong experience in signal integrity modeling and simulation (HFSS or similar EM tools)
Deep understanding of high-frequency / broadband design
Solid understanding of multi-layer PCB design and signal behavior
Knowledge of PCB materials and their electrical and physical properties
Experience with lab measurements (VNA, high-speed characterization)
Background in cryogenic technologies or strong interest in developing expertise in this area
Ways to stand out from the crowd:
Experience working on low-loss / ultra-high-speed interconnects
Background in materials modeling or SI-material correlation
Experience in extreme environments (cryogenic, thermal, or reliability-driven design)
Track record of correlating simulation to hardware measurements
Strong cross-functional experience with PCB, package, and system teams
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 3, 2026.This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.How we rate this
Senior Signal Integrity Engineer – Cryogenic Interconnects at NVIDIA rates 9 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
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